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 www.philschmid.de
Extended Guide: Instruction-tune Llama 2
| | zackproser.com
How to Fine-tune Llama 3.1 on Lightning.ai with Torchtune
1.2 parsecs away

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| | One of the better Jupyter Notebooks to GPU-backed environment experiences I've had...
| | raw.sh
Batched reward model inference and Best-of-N sampling | raw.sh
1.8 parsecs away

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| | Building a reward model API with dynamic batching, with complete Python implementation. Demonstrates 20% accuracy gains using Best-of-N sampling for inference-time scaling.
| | www.confident-ai.com
The Ultimate Guide to Fine-Tune LLaMA 3, With LLM Evaluations - Confident AI
0.8 parsecs away

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| | In this article, we'll walkthrough how to fine-tune and evaluate a LLaMA-2 model using Hugging Face and DeepEval
| | www.evidentlyai.com
AMA with Ben Wilson: planning ML projects, AutoML, and ML deployment at scale
18.1 parsecs away

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| In this blog, we recap the Ask-Me-Anything session with Ben Wilson. We chatted about AutoML use cases, deploying ML models to production, and how one can learn about ML engineering.